The neural mechanisms underlying self-regulation in alcohol use disorders (AUD) with and without comorbid cigarette smoking are clinically important yet unsolved issues of practical importance to substance abuse in general and to alcohol relapse and treatment in particular. This proposal aims to explore the relationships of self-regulation to resting brain neural circuitry (by functional connectivity) and neuronal viabiliy (by cortical metabolite concentrations) in large-scale neurocognitive networks and in the reward network of individuals with AUD compared with healthy controls. This study will use multi-modal data acquired as part of NIH-funded research projects and serve as a training vehicle for Dr. Murray to gain clinical research experience in multi- modal neuroimaging of individuals with AUD. We will relate various measures of self-regulation to within- network functional connectivity from resting state-functional MRI (rsfMRI) and to select metabolite concentrations (primarily N-acetylaspartate and glutamate) from localized proton magnetic resonance spectroscopy (1H MRS) in AUD individuals and healthy controls for comparison. We will determine the impact of a clinically relevant behavior (self-regulation) to both the strength of functional connectivity within brain networks (neurocognitive and reward networks) and the level of regional metabolite concentrations within major nodes of these networks in 4030 AUD individuals at one month of abstinence and in 2030 healthy controls. It is hypothesized that short-term abstinent AUD individuals will have altered functional connectivity within brain networks that is associated with poor self-regulation and low metabolite concentrations compared with healthy controls, and that these relationships are critically influenced by chronic cigarette smoking. In further exploratory analyses, the 15 smoking AUD individuals will be compared with a group of 15 smoking opioid dependent individuals precisely to test the specificity of the findings to AUD. The interrelationships between self-regulation, functional connectivity, and cortical metabolite concentrations are predicted to identify a set of measures that illuminate unique neural correlates of substance use behavior. Understanding the link between functional network connectivity and its associations to both self-regulation and metabolic activity within these networks promises to provide novel information regarding relapse risk proneness and improved treatment approaches in alcohol and tobacco use disorders.